Stability and convergence analysis of intelligent control algorithm based on fuzzy set theory in dynamic environment

Intelligent control algorithms in dynamic multi-obstacle scenarios are prone to the problem of poor stability and reliability of their own motion. In order to solve the above core problems, firstly, the fuzzy set theory is used to adjust the three control parameters of PID control to realize the adaptive adjustment of the system when facing uncertain changes. Secondly, for the defects of fuzzy control summary time is too long, the immunity algorithm with excellent feedback is combined with fuzzy control to realize more accurate control of the controlled object with less summary time, which improves the efficiency and stability of the control system. Based on the generalized Routh criterion, the theoretical determination steps of the stability and convergence of the intelligent controller in this paper are given to provide a guarantee for the safe operation of the intelligent control system. The output trajectory oscillation range of the controller based on fuzzy immune PID algorithm designed in this paper is within -5~1, which is smaller than that of the traditional controller output trajectory. And the optimization algorithm in this paper has a very small error in tracking maximum power in a variety of local shading environments, and the oscillation range in dynamic environment is within 0.4W, which are smaller than the oscillation interval under the fuzzy control algorithm and immune algorithm alone. It shows that the optimized hybrid algorithm in this paper has important research significance for the development of intelligent control systems.